Senior Consultant AI/ML

Remote

Pay: Pay not listed
Work setting: Remote — work setting source
Listed location: Remote
Read the full posting
Employment: Not stated

What you’ll work on

Define and own the AI/ML roadmap for end-to-end claims automation
Architect the claims AI pipeline, from intake and coding validation to fraud detection and payment
Lead customer workshops to scope and prioritize agentic AI use cases
Implement agents with Strands SDK and Bedrock AgentCore Runtime
Design and implement RAG architectures on Bedrock Knowledge Bases

From the employer’s posting

Define and own the AI/ML solution roadmap for end-to-end claims automation

Architect the AI/ML pipeline: claims intake , data extraction, eligibility verification, medical coding validation, auto-adjudication, fraud detection, and payment processing

Lead technical workshops with customer to identify, prioritize, and scope agentic AI use cases

Implement agents using Strands SDK (or equivalent) with Bedrock AgentCore Runtime

Design and implement RAG architectures using Bedrock Knowledge Bases and vector stores

What you’ll bring

All qualifications

Core experience

10+ years in technology delivery
5+ years leading AI/ML programs at enterprise scale
Deep AI/ML engineering expertise
Healthcare domain expertise
Experience with AWS Bedrock AgentCore and supporting services

Qualification wording

10+ years in technology delivery

5+ years leading AI/ML programs at enterprise scale

combine deep AI/ML engineering expertise

healthcare domain expertise

using AWS Bedrock AgentCore and supporting services

Apply at CG Infinity

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Status in our records: Live
First seen by us: Oct 16, 202623 days ago
Recorded sightings: 26
Last seen by us: Nov 8, 2026

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How this job compares

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Day 23

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CG Infinity is hiring

3 open jobs

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Hiring record

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Where the posting names them

Senior Consultant AI/ML 100% Remote- 10+ years in technology delivery with 5+ years leading AI/ML programs at enterprise scale to serve as the Subject Matter Expert for the Agentic AI workstream. This resource will lead customer-facing conversations to understand use cases, design agentic AI solutions, and drive implementation using AWS Bedrock AgentCore and supporting services. The consultant must combine deep AI/ML engineering expertise with the ability to act as a trusted technical advisor to customer stakeholders. The consultant will own end-to-end delivery of an enterprise-scale AI/ML solution that fully automates the healthcare claims processing lifecycles from claims intake and adjudication through payment and denial management. This role requires a blend of technical depth in AI/ML, healthcare domain expertise, and strong program leadership to drive transformation at scale. - Define and own the AI/ML solution roadmap for end-to-end claims automation, aligning with the customer’s enterprise transformation goals

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Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.

August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025: $140,300
Expected change, 2025 to 2035: 21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

Senior Consultant AI/ML
100% Remote

10+ years in technology delivery with 5+ years leading AI/ML programs at enterprise scale to serve as the Subject Matter Expert for the Agentic AI workstream. This resource will lead customer-facing conversations to understand use cases, design agentic AI solutions, and drive implementation using AWS Bedrock AgentCore and supporting services. The consultant must combine deep AI/ML engineering expertise with the ability to act as a trusted technical advisor to customer stakeholders. The consultant will own end-to-end delivery of an enterprise-scale AI/ML solution that fully automates the healthcare claims processing lifecycles from claims intake and adjudication through payment and denial management. This role requires a blend of technical depth in AI/ML, healthcare domain expertise, and strong program leadership to drive transformation at scale.
Define and own the AI/ML solution roadmap for end-to-end claims automation, aligning with the customer’s enterprise transformation goals
Work with cross-functional teams (data scientists, AI/ML engineers, cloud architects, business analysts, and SMEs) to deliver production-grade AI/ML solutions
Serve as the primary point of accountability for project delivery, risk management, and stakeholder communication
Architect the AI/ML pipeline: claims intake , data extraction, eligibility verification, medical coding validation, auto-adjudication, fraud detection, and payment processing
Oversee model development, training, validation, and deployment across the claims lifecycle
Ensure solution scalability to handle enterprise-level claim volumes (millions of claims/month)
Define AI/MLOps strategy including model monitoring, retraining pipelines, drift detection, and testing
Lead technical workshops with customer to identify, prioritize, and scope agentic AI use cases
Design agentic patterns (ReAct, tool-use, multi-agent orchestration) mapped to customer business problems
Build and operate evaluation pipelines for agentic systems (correctness, safety, latency, cost)
Implement agents using Strands SDK (or equivalent) with Bedrock AgentCore Runtime
Design and implement RAG architectures using Bedrock Knowledge Bases and vector stores
Instrument agents for tracing, monitoring, and debugging via Bedrock AgentCore Observability

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